AIMC Topic: Tomography, Emission-Computed, Single-Photon

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Interpretation of SPECT wall motion with deep learning.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
OBJECTIVES: We sought to develop a novel deep learning (DL) workflow to interpret single-photon emission computed tomography (SPECT) wall motion.

Presynaptic Dopaminergic Imaging Characterizes Patients with REM Sleep Behavior Disorder Due to Synucleinopathy.

Annals of neurology
OBJECTIVE: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy ...

Artificial intelligence in immunotherapy PET/SPECT imaging.

European radiology
OBJECTIVE: Immunotherapy has dramatically altered the therapeutic landscape for oncology, but more research is needed to identify patients who are likely to achieve durable clinical benefit and those who may develop unacceptable side effects. We inve...

Artificial Intelligence for PET and SPECT Image Enhancement.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Nuclear medicine imaging modalities such as PET and SPECT are confounded by high noise levels and low spatial resolution, necessitating postreconstruction image enhancement to improve their quality and quantitative accuracy. Artificial intelligence (...

Deep learning approach using SPECT-to-PET translation for attenuation correction in CT-less myocardial perfusion SPECT imaging.

Annals of nuclear medicine
OBJECTIVE: Deep learning approaches have attracted attention for improving the scoring accuracy in computed tomography-less single photon emission computed tomography (SPECT). In this study, we proposed a novel deep learning approach referring to pos...

Automated identification of uncertain cases in deep learning-based classification of dopamine transporter SPECT to improve clinical utility and acceptance.

European journal of nuclear medicine and molecular imaging
PURPOSE: Deep convolutional neural networks (CNN) are promising for automatic classification of dopamine transporter (DAT)-SPECT images. Reporting the certainty of CNN-based decisions is highly desired to flag cases that might be misclassified and, t...

Ultra-fast whole-body bone tomoscintigraphies achieved with a high-sensitivity 360° CZT camera and a dedicated deep-learning noise reduction algorithm.

European journal of nuclear medicine and molecular imaging
UNLABELLED: This study aimed to determine whether the whole-body bone Single Photon Emission Computed Tomography (SPECT) recording times of around 10 min, routinely provided by a high-sensitivity 360° cadmium and zinc telluride (CZT) camera, can be f...